Articles | Volume 29, issue 14
https://doi.org/10.5194/hess-29-3315-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-3315-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Jul 2025
Research article |
| 28 Jul 2025
| 28 Jul 2025
Impacts of inter-basin water diversion projects on the feedback loops of water supply–hydropower generation–environment conservation nexus
Jiaoyang Wang
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, China
Dedi Liu
CORRESPONDING AUTHOR
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, 430072, China
Department of Earth Science, University of the Western Cape, Bellville, Republic of South Africa
Shenglian Guo
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, China
Lihua Xiong
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, China
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, China
Hua Chen
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, China
Jie Chen
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, China
Jiabo Yin
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, China
Hubei Provincial Key Lab of Water System Science for Sponge City Construction, Wuhan University, Wuhan, 430072, China
Yuling Zhang
State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, China
Related authors
Jiayu Zhang, Dedi Liu, Jiaoyang Wang, Feng Yue, Hanxu Liang, Zhengbo Peng, and Wei Guan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2734, https://doi.org/10.5194/egusphere-2025-2734, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Water use is often estimated with coarse data that overlook spatial heterogeneity, limiting effective water planning. This study proposes a framework to simulate water use at multiple spatial scales across China, combining a grid-based approach and uncertainty analysis. It finds that both the model structure and spatial scale affect. The framework reveals detailed patterns in water use and can guide smarter water resources management.
Jiayu Zhang, Dedi Liu, Jiaoyang Wang, Feng Yue, Hanxu Liang, Zhengbo Peng, and Wei Guan
EGUsphere, https://doi.org/10.5194/egusphere-2025-2734, https://doi.org/10.5194/egusphere-2025-2734, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Water use is often estimated with coarse data that overlook spatial heterogeneity, limiting effective water planning. This study proposes a framework to simulate water use at multiple spatial scales across China, combining a grid-based approach and uncertainty analysis. It finds that both the model structure and spatial scale affect. The framework reveals detailed patterns in water use and can guide smarter water resources management.
Chao Ma, Weifeng Hao, Qing Cheng, Fan Ye, Ying Qu, Jiabo Yin, Fang Xu, Haojian Wu, and Fei Li
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-79, https://doi.org/10.5194/essd-2025-79, 2025
Revised manuscript accepted for ESSD
Short summary
Short summary
Antarctic sea ice albedo is a key factor influencing the energy balance of the cryosphere. Here we present a daily 1 km shortwave albedo product for Antarctic sea ice from 2012 to 2021, based on VIIRS reflectance data. Additionally, we reconstructed the albedo for missing pixels due to cloud cover. This dataset can be used to assess changes in Antarctic sea ice, radiation budget, and the strength of sea ice albedo feedback mechanisms, as well as their potential interconnections.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Göktürk
Hydrol. Earth Syst. Sci., 29, 2133–2152, https://doi.org/10.5194/hess-29-2133-2025, https://doi.org/10.5194/hess-29-2133-2025, 2025
Short summary
Short summary
We compared hourly and daily extreme precipitation across Norway from HARMONIE Climate models at convection-permitting 3 km (HCLIM3) and 12 km (HCLIM12) resolutions. HCLIM3 more accurately captures the extremes in most regions and seasons (except in summer). Its advantages are more pronounced for hourly extremes than for daily extremes. The results highlight the value of convection-permitting models in improving extreme-precipitation predictions and in helping the local society brace for extreme weather.
Qiumei Ma, Chengyu Xie, Zheng Duan, Yanke Zhang, Lihua Xiong, and Chong-Yu Xu
EGUsphere, https://doi.org/10.5194/egusphere-2025-679, https://doi.org/10.5194/egusphere-2025-679, 2025
Short summary
Short summary
We propose a method to estimate the reservoir WLS curve based on the capacity loss induced by sediment accumulation and further assess the potential negative impact caused by outdated design WLS curve on flood regulation risks. The findings highlight that when storage capacity is considerably reduced, continued use of the existing design WLS curve may significantly underestimate, thus posing potential safety hazards to the reservoir itself and downstream flood protection objects.
Xin Xiang, Shenglian Guo, Chenglong Li, and Yun Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-279, https://doi.org/10.5194/egusphere-2025-279, 2025
Short summary
Short summary
Deep learning models excel in hydrological simulations but lack physical foundations. We combine the Xinanjiang model’s principles into recurrent neural network units, forming a physical-based XAJRNN layer. Combined with LSTM layers, we propose an explainable deep learning model. The model shows low peak errors and minimal timing differences. The model improves accuracy and interpretability, offering new insights for combining deep learning and hydrological models in flood forecasting.
Ruikang Zhang, Dedi Liu, Lihua Xiong, Jie Chen, Hua Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 28, 5229–5247, https://doi.org/10.5194/hess-28-5229-2024, https://doi.org/10.5194/hess-28-5229-2024, 2024
Short summary
Short summary
Flash flood warnings cannot be effective without people’s responses to them. We propose a method to determine the threshold of issuing warnings based on a people’s response process simulation. The results show that adjusting the warning threshold according to people’s tolerance levels to the failed warnings can improve warning effectiveness, but the prerequisite is to increase forecasting accuracy and decrease forecasting variance.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
Short summary
Short summary
Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
Short summary
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Jinghua Xiong, Shenglian Guo, Abhishek, Jiabo Yin, Chongyu Xu, Jun Wang, and Jing Guo
Hydrol. Earth Syst. Sci., 28, 1873–1895, https://doi.org/10.5194/hess-28-1873-2024, https://doi.org/10.5194/hess-28-1873-2024, 2024
Short summary
Short summary
Temporal variability and spatial heterogeneity of climate systems challenge accurate estimation of probable maximum precipitation (PMP) in China. We use high-resolution precipitation data and climate models to explore the variability, trends, and shifts of PMP under climate change. Validated with multi-source estimations, our observations and simulations show significant spatiotemporal divergence of PMP over the country, which is projected to amplify in future due to land–atmosphere coupling.
Qian Lin, Jie Chen, and Deliang Chen
EGUsphere, https://doi.org/10.5194/egusphere-2024-826, https://doi.org/10.5194/egusphere-2024-826, 2024
Preprint archived
Short summary
Short summary
Glaciers of the Tibetan Plateau (TP) have experienced widespread retreat in recent decades, but impacts of glacier changes that have occurred on regional climate, including precipitation, is still unknown. Thus, this study addressed this knowledge gap, and found that glacier changes exert a more pronounced impact on summer extreme precipitation events than mean precipitation over the TP. This provides a certain theoretical reference for the further improvement of long-term glacier projection.
Jiabo Yin, Louise J. Slater, Abdou Khouakhi, Le Yu, Pan Liu, Fupeng Li, Yadu Pokhrel, and Pierre Gentine
Earth Syst. Sci. Data, 15, 5597–5615, https://doi.org/10.5194/essd-15-5597-2023, https://doi.org/10.5194/essd-15-5597-2023, 2023
Short summary
Short summary
This study presents long-term (i.e., 1940–2022) and high-resolution (i.e., 0.25°) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). Our proposed GTWS-MLrec performs overall as well as, or is more reliable than, previous TWS datasets.
Jinghua Xiong, Abhishek, Li Xu, Hrishikesh A. Chandanpurkar, James S. Famiglietti, Chong Zhang, Gionata Ghiggi, Shenglian Guo, Yun Pan, and Bramha Dutt Vishwakarma
Earth Syst. Sci. Data, 15, 4571–4597, https://doi.org/10.5194/essd-15-4571-2023, https://doi.org/10.5194/essd-15-4571-2023, 2023
Short summary
Short summary
To overcome the shortcomings associated with limited spatiotemporal coverage, input data quality, and model simplifications in prevailing evaporation (ET) estimates, we developed an ensemble of 4669 unique terrestrial ET subsets using an independent mass balance approach. Long-term mean annual ET is within 500–600 mm yr−1 with a unimodal seasonal cycle and several piecewise trends during 2002–2021. The uncertainty-constrained results underpin the notion of increasing ET in a warming climate.
Youjiang Shen, Karina Nielsen, Menaka Revel, Dedi Liu, and Dai Yamazaki
Earth Syst. Sci. Data, 15, 2781–2808, https://doi.org/10.5194/essd-15-2781-2023, https://doi.org/10.5194/essd-15-2781-2023, 2023
Short summary
Short summary
Res-CN fills a gap in a comprehensive and extensive dataset of reservoir-catchment characteristics for 3254 Chinese reservoirs with 512 catchment-level attributes and significantly enhanced spatial and temporal coverage (e.g., 67 % increase in water level and 225 % in storage anomaly) of time series of reservoir water level (data available for 20 % of 3254 reservoirs), water area (99 %), storage anomaly (92 %), and evaporation (98 %), supporting a wide range of applications and disciplines.
Youjiang Shen, Dedi Liu, Liguang Jiang, Karina Nielsen, Jiabo Yin, Jun Liu, and Peter Bauer-Gottwein
Earth Syst. Sci. Data, 14, 5671–5694, https://doi.org/10.5194/essd-14-5671-2022, https://doi.org/10.5194/essd-14-5671-2022, 2022
Short summary
Short summary
A data gap of 338 Chinese reservoirs with their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) during 2010–2021. Validation against the in situ observations of 93 reservoirs indicates the relatively high accuracy and reliability of the datasets. The unique and novel remotely sensed dataset would benefit studies involving many aspects (e.g., hydrological models, water resources related studies, and more).
Jinghua Xiong, Shenglian Guo, Abhishek, Jie Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 26, 6457–6476, https://doi.org/10.5194/hess-26-6457-2022, https://doi.org/10.5194/hess-26-6457-2022, 2022
Short summary
Short summary
Although the "dry gets drier, and wet gets wetter (DDWW)" paradigm is prevalent in summarizing wetting and drying trends, we show that only 11.01 %–40.84 % of the global land confirms and 10.21 %–35.43 % contradicts the paradigm during 1985–2014 from a terrestrial water storage change perspective. Similar proportions that intensify with the increasing emission scenarios persist until the end of the 21st century. Findings benefit understanding of global hydrological responses to climate change.
Yunfan Zhang, Lei Cheng, Lu Zhang, Shujing Qin, Liu Liu, Pan Liu, and Yanghe Liu
Hydrol. Earth Syst. Sci., 26, 6379–6397, https://doi.org/10.5194/hess-26-6379-2022, https://doi.org/10.5194/hess-26-6379-2022, 2022
Short summary
Short summary
Multiyear drought has been demonstrated to cause non-stationary rainfall–runoff relationship. But whether changes can invalidate the most fundamental method (i.e., paired-catchment method (PCM)) for separating vegetation change impacts is still unknown. Using paired-catchment data with 10-year drought, PCM is shown to still be reliable even in catchments with non-stationarity. A new framework is further proposed to separate impacts of two non-stationary drivers, using paired-catchment data.
Wei Li, Jie Chen, Lu Li, Yvan J. Orsolini, Yiheng Xiang, Retish Senan, and Patricia de Rosnay
The Cryosphere, 16, 4985–5000, https://doi.org/10.5194/tc-16-4985-2022, https://doi.org/10.5194/tc-16-4985-2022, 2022
Short summary
Short summary
Snow assimilation over the Tibetan Plateau (TP) may influence seasonal forecasts over this region. To investigate the impacts of snow assimilation on the seasonal forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer in 2018. The results show that snow assimilation can improve seasonal forecasts over the TP through the interaction between land and atmosphere.
Jing Tian, Zhengke Pan, Shenglian Guo, Jiabo Yin, Yanlai Zhou, and Jun Wang
Hydrol. Earth Syst. Sci., 26, 4853–4874, https://doi.org/10.5194/hess-26-4853-2022, https://doi.org/10.5194/hess-26-4853-2022, 2022
Short summary
Short summary
Most of the literature has focused on the runoff response to climate change, while neglecting the impacts of the potential variation in the active catchment water storage capacity (ACWSC) that plays an essential role in the transfer of climate inputs to the catchment runoff. This study aims to systematically identify the response of the ACWSC to a long-term meteorological drought and asymptotic climate change.
Shanlin Tong, Weiguang Wang, Jie Chen, Chong-Yu Xu, Hisashi Sato, and Guoqing Wang
Geosci. Model Dev., 15, 7075–7098, https://doi.org/10.5194/gmd-15-7075-2022, https://doi.org/10.5194/gmd-15-7075-2022, 2022
Short summary
Short summary
Plant carbon storage potential is central to moderate atmospheric CO2 concentration buildup and mitigation of climate change. There is an ongoing debate about the main driver of carbon storage. To reconcile this discrepancy, we use SEIB-DGVM to investigate the trend and response mechanism of carbon stock fractions among water limitation regions. Results show that the impact of CO2 and temperature on carbon stock depends on water limitation, offering a new perspective on carbon–water coupling.
Kang Xie, Pan Liu, Qian Xia, Xiao Li, Weibo Liu, Xiaojing Zhang, Lei Cheng, Guoqing Wang, and Jianyun Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-217, https://doi.org/10.5194/essd-2022-217, 2022
Revised manuscript not accepted
Short summary
Short summary
There are currently no available common datasets of the Soil moisture storage capacity (SMSC) on a global scale, especially for hydrological models. Here, we produce a dataset of the SMSC parameter for global hydrological models. The global SMSC is constructed based on the deep residual network at 0.5° resolution. SMSC products are validated on global grids and typical catchments from different climatic regions.
Yujie Zeng, Dedi Liu, Shenglian Guo, Lihua Xiong, Pan Liu, Jiabo Yin, and Zhenhui Wu
Hydrol. Earth Syst. Sci., 26, 3965–3988, https://doi.org/10.5194/hess-26-3965-2022, https://doi.org/10.5194/hess-26-3965-2022, 2022
Short summary
Short summary
The sustainability of the water–energy–food (WEF) nexus remains challenge, as interactions between WEF and human sensitivity and water resource allocation in water systems are often neglected. We incorporated human sensitivity and water resource allocation into a WEF nexus and assessed their impacts on the integrated system. This study can contribute to understanding the interactions across the water–energy–food–society nexus and improving the efficiency of resource management.
Jiacheng Chen, Jie Chen, Xunchang John Zhang, Peiyi Peng, and Camille Risi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-460, https://doi.org/10.5194/essd-2021-460, 2022
Manuscript not accepted for further review
Short summary
Short summary
To make full use of the advantages of isotope observations and simulations, this study generates a new dataset by integrating multi-GCM data based on data fusion and bias correction methods. This dataset contains monthly δ18Op over mainland China for the 1870–2017 period with a spatial resolution of 50–60 km. The built isoscape shows similar spatial and temporal distribution characteristics to observations, which is reliable and useful to extend the time and space of observations in China.
Jinghua Xiong, Shenglian Guo, Jie Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-645, https://doi.org/10.5194/hess-2021-645, 2022
Manuscript not accepted for further review
Short summary
Short summary
Although the “dry gets drier and wet gets wetter” (DDWW) paradigm is widely used to describe the trends in wetting and drying globally, we show that 27.1 % of global land agrees with the paradigm, while 22.4 % shows the opposite pattern during the period 1985–2014 from the perspective of terrestrial water storage change. Similar percentages are discovered under different scenarios during the future period. Our findings will benefit the understanding of hydrological responses under climate change.
Wei Li, Lu Li, Jie Chen, Qian Lin, and Hua Chen
Hydrol. Earth Syst. Sci., 25, 4531–4548, https://doi.org/10.5194/hess-25-4531-2021, https://doi.org/10.5194/hess-25-4531-2021, 2021
Short summary
Short summary
Reforestation can influence climate, but the sensitivity of summer rainfall to reforestation is rarely investigated. We take two reforestation scenarios to assess the impacts of reforestation on summer rainfall under different reforestation proportions and explore the potential mechanisms. This study concludes that reforestation increases summer rainfall amount and extremes through thermodynamics processes, and the effects are more pronounced in populated areas than over the whole basin.
Ren Wang, Pierre Gentine, Jiabo Yin, Lijuan Chen, Jianyao Chen, and Longhui Li
Hydrol. Earth Syst. Sci., 25, 3805–3818, https://doi.org/10.5194/hess-25-3805-2021, https://doi.org/10.5194/hess-25-3805-2021, 2021
Short summary
Short summary
Assessment of changes in the global water cycle has been a challenge. This study estimated long-term global latent heat and sensible heat fluxes for recent decades using machine learning and ground observations. The results found that the decline in evaporative fraction was typically accompanied by an increase in long-term runoff in over 27.06 % of the global land areas. The observation-driven findings emphasized that surface vegetation has great impacts in regulating water and energy cycles.
Xiaojing Zhang and Pan Liu
Hydrol. Earth Syst. Sci., 25, 711–733, https://doi.org/10.5194/hess-25-711-2021, https://doi.org/10.5194/hess-25-711-2021, 2021
Short summary
Short summary
Rainfall–runoff models are useful tools for streamflow simulation. However, efforts are needed to investigate how their parameters vary in response to climate changes and human activities. Thus, this study proposes a new method for estimating time-varying parameters, by considering both simulation accuracy and parameter continuity. The results show the proposed method is effective for identifying temporal variations of parameters and can simultaneously provide good streamflow simulation.
Yunfan Zhang, Lei Cheng, Lu Zhang, Shujing Qin, Liu Liu, Pan Liu, Yanghe Liu, and Jun Xia
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-5, https://doi.org/10.5194/hess-2021-5, 2021
Manuscript not accepted for further review
Short summary
Short summary
We use statistical methods and data assimilation method with physical model to verify that prolonged drought can induce non-stationarity in the control catchment rainfall-runoff relationship, which causes three inconsistent results at the Red Hill paired-catchment site. The findings are fundamental to correctly use long-term historical data and effectively assess ecohydrological impacts of vegetation change given that extreme climate events are projected to occur more frequently in the future.
Zhengke Pan, Pan Liu, Chong-Yu Xu, Lei Cheng, Jing Tian, Shujie Cheng, and Kang Xie
Hydrol. Earth Syst. Sci., 24, 4369–4387, https://doi.org/10.5194/hess-24-4369-2020, https://doi.org/10.5194/hess-24-4369-2020, 2020
Short summary
Short summary
This study aims to identify the response of catchment water storage capacity (CWSC) to meteorological drought by examining the changes of hydrological-model parameters after drought events. This study improves our understanding of possible changes in the CWSC induced by a prolonged meteorological drought, which will help improve our ability to simulate the hydrological system under climate change.
Cited articles
Bai, T., Li, L., Mu, P., Pan, B., and Liu, J.: Impact of Climate Change on Water Transfer Scale of Inter-basin Water Diversion Project, Water Resour. Manag., 37, 2505–2525, https://doi.org/10.1007/s11269-022-03387-8, 2023.
Bland, M. J. and Altman, G.: Statistical methods for assessing agreement between two methods of clinical measurement, Lancet, 1, 307–310, https://doi.org/10.1016/S0140-6736(86)90837-8, 1986.
Botelho, A., Ferreira, P., Lima, F., Pinto, L. M. C., and Sousa, S.: Assessment of the environmental impacts associated with hydropower, Renew. Sust. Energ. Rev., 70, 896–904. https://doi.org/10.1016/j.rser.2016.11.271, 2017.
Chen, Y., Mei, Y., Cai, H., and Xu, X.: Multi-objective optimal operation of key reservoirs in Ganjiang River oriented to power generation, water supply and ecology, J. Hydraul. Eng., 49, 628–638, https://doi.org/10.13243/j.cnki.slxb.20180130, 2018 (in Chinese).
Chen, L., Huang, K. D., Zhou, J. Z., Duan, H. F., Zhang, J. H., Wang, D. W., and Qiu, H.: Multiple-risk assessment of water supply, hydropower and environment nexus in the water resources system, J. Clean. Prod., 268, 122057, https://doi.org/10.1016/j.jclepro.2020.122057, 2020.
Chung, M., Frank, K. A., Pokhrel, Y., Dietz, T., and Liu, J.: Natural infrastructure in sustaining global urban freshwater ecosystem services, Nat. Sustain., 4, 1068–1075, https://doi.org/10.1038/s41893-021-00786-4, 2021.
Conway, D., van Garderen, E. A., Deryng, D., Dorling, S., Krueger, T., Landman, W., Lankford, B., Lebek, K., Osborn, T., Ringler, C., Thurlow, J., Zhu, T., and Dalin, C.: Climate and southern Africa's water-energy-food nexus, Nat. Clim. Change, 5, 837–846, https://doi.org/10.1038/NCLIMATE2735, 2015.
Dong, J., Chen, X., Li, Y., Gao, M., Wei, L., Tangdamrongsu, N., Crow, T. W.: Inter-Basin Water Transfer Effectively Compensates for Regional Unsustainable Water Use, Water Resour. Res., 59, e2023WR035129, https://doi.org/10.1029/2023WR035129, 2023.
Dong, Q., Zhang, X., Chen, Y., and Fang, D.: Dynamic Management of a Water Resources-Socioeconomic-Environmental System Based on Feedbacks Using System Dynamics, Water Resour. Manag., 33, 2093–2108, https://doi.org/10.1007/s11269-019-02233-8, 2019.
Doummar, J., Massoud, M. A., Khoury, R., and Khawlie, M.: Optimal Water Resources Management: Case of Lower Litani River, Lebanon, Water Resour. Manag., 23, 2343–2360, https://doi.org/10.1007/s11269-008-9384-z, 2009.
Endo, A., Tsurita, I., Burnett, K., and Orencio, P. M.: A review of the current state of research on the water, energy, and food nexus, J. Hydrol. Reg. Stud., 11, 20–30, https://doi.org/10.1016/j.ejrh.2015.11.010, 2017.
FAO: The water-energy-food nexus-A new approach in support of food security and sustainable agriculture, Food and Agriculture Organization of the United Nations, Rome, 2014.
Feng, M., Liu, P., Guo, S., Yu, J. D., Cheng, L., Yang, G., and Xie, A.: Adapting reservoir operations to the nexus across water supply, power generation, and environment systems: An explanatory tool for policy makers, J. Hydrol., 574, 257–275, https://doi.org/10.1016/j.jhydrol.2019.04.048, 2019.
Franchini, M., Ventaglio, E., and Bonoli, A.: A Procedurefor Evaluating the Compatibility of Surface Water Resourceswith Environmental and Human Requirements, Water Resour. Manag., 25, 3613–3634, https://doi.org/10.1007/s11269-011-9873-3, 2011.
Gao, Y., Xiong, W., and Wang, C.: numerical modelling of a dam-regulated river network for balancing water supply and ecological flow downstream, Water, 15, 1962, https://doi.org/10.3390/W15101962, 2023.
Gou, J., Miao, C., Duan, Q., Tang, Q., Di, Z., Liao, W., Wu, J., and Zhou, R.: Sensitivity Analysis-Based Automatic Parameter Calibration of the VIC Model for Streamflow Simulations Over China, Water Resour. Res., 56, e2019WR025968, https://doi.org/10.1029/2019WR025968, 2020.
Gupta, D. A.: Implication of environmental flows in river basin management, Phys. Chem. Earth., 33, 298–303, https://doi.org/10.1016/j.pce.2008.02.004, 2008.
Hansen, M., DeFries, R., Townshend, J. R. G., and Sohlberg, R.: UMD Global Land Cover Classification, 1 Kilometer, 1.0, Department of Geography, University of Maryland, College Park, 1981–1994, 1998.
He, Y. Y., Feng, X. Q., and Wang, X. B.: Study of water resources allocation model of North Hubei Water Transfer Project and operation schemes comparison, Express Water Resources & Hydropower Information, 41, 26–29, https://doi.org/10.15974/j.cnki.slsdkb.2020.10.005, 2020.
Hong, X., Guo, S., Le Wang, Yang, G., Liu, D., Guo, H., and Wang, J.: Evaluating Water Supply Risk in the Middle and Lower Reaches of Hanjiang River Basin Based on an Integrated Optimal Water Resources Allocation Model, Water, 8, 364, https://doi.org/10.3390/w8090364, 2016.
Jiang, Z., Wu, W., Qin, H., and Zhou, J.: Credibility theory based panoramic fuzzy risk analysis of hydropower station operation near the boundary, J. Hydrol., 565, 474–488, https://doi.org/10.1016/j.jhydrol.2018.08.048, 2018.
Kattel, G. R., Shang, W., Wang, Z., and Langford, J.: China's South-to-North Water Diversion Project Empowers Sustainable Water Resources System in the North, Sustainability, 11, 3735, https://doi.org/10.3390/su11133735, 2019.
Keyhanpour, M. J., Jahromi, S. H. M., and Ebrahimi, H.: System dynamics model of sustainable water resources management using the Nexus Water-Food-Energy approach, Ain Shams Eng. J., 12, 1267–1281, https://doi.org/10.1109/MCDM.2007.369107, 2021.
Khalkhali, M., Westphal, K., and Mo, W.: The water-energy nexus at water supply and its implications on the integrated water and energy management, Sci. Total Environ., 636, 1257–1267, https://doi.org/10.1016/j.scitotenv.2018.04.408, 2018.
Koohi, S., Azizian, A., and Brocca, L.: Calibration of a Distributed Hydrological Model (VIC-3L) Based on Global Water Resources Reanalysis Datasets, Water Resour. Manag., 36, 1287–1306, https://doi.org/10.1007/s11269-022-03081-9, 2022.
Li, C. and Kang, L.: A New Modified Tennant Method with Spatial-Temporal Variability, Water Resour. Manag., 28, 4911–4926, https://doi.org/10.1007/s11269-014-0746-4, 2014.
Li, C., Kang, L., Zhang S., and Zhou, L.: A Modied FDC Method with Multi-level Ecological Flow Criteria, J. Yangtze River Sci. Res. Inst., 32, 1–6, https://doi.org/10.11988/ckyyb.20140814, 2015 (in Chinese).
Li, Y., Xiong, W., Zhang, W., Wang, C., and Wang, P.: Life cycle assessment of water supply alternatives in water-receiving areas of the South-to-North Water Diversion Project in China, Water Res., 89, 9–19, https://doi.org/10.1007/s11269-011-9873-3, 2016.
Liang, X., Lettenmaier, D. P.: Wood, E. F., and Burges, S. J.: A Simple Hydrologically Based Model Of Land-Surface Water And Energy Fluxes For General-Circulation Models, J. Geophys. Res.-Atmos., 99, 14415–14428, https://doi.org/10.1029/94JD00483, 1994.
Liu, D., Guo, S., Shao, Q., Liu, P., Xiong, L., Wang, L., Hong, X., Xu, Y., and Wang, Z.: Assessing the effects of adaptation measures on optimal water resources allocation under varied water availability conditions, J. Hydrol., 556, 759–774, https://doi.org/10.1016/j.jhydrol.2017.12.002, 2018.
Liu, J., Yuan, X., Zeng, J., Jiao, Y., Li, Y., Zhong, L., and Yao, L.: Ensemble streamflow forecasting over a cascade reservoir catchment with integrated hydrometeorological modeling and machine learning, Hydrol. Earth Syst. Sci., 26, 265–278, https://doi.org/10.5194/hess-26-265-2022, 2022.
Long, D., Yang, W., Scanlon, B. R., Zhao, J., Liu, D., Burek, P., Pan, Y., You, L., and Wada, Y.: South-to-North Water Diversion stabilizing Beijing's groundwater levels, Nat. Commun., 11, 3665, https://doi.org/10.1038/s41467-020-17428-6, 2020.
MacGregor, J. J.: Natural Resources in the United States, Nature, 200, 518–520, https://doi.org/10.1038/200518a0, 1963.
Mansour, F., Al-Hindi, M., Najm, M. A., and Yassine, A.: The water energy food nexus: A multi-objective optimization tool, Comput. Chem. Eng., 187, 108718, https://doi.org/10.1016/J.COMPCHEMENG.2024.108718, 2024.
Martinez, J., Deng, Z., Tian, C., Mueller, R., Phonekhampheng, O., Singhanouvong, D., Thorncraft, G., Phommavong, T., and Phommachan, K.: In situ characterization of turbine hydraulic environment to support development of fish-friendly hydropower guidelines in the lower Mekong River region, Ecol. Eng., 133, 88–97, https://doi.org/10.1016/j.ecoleng.2019.04.028, 2019.
Mok, K. Y., Shen, G., and Yang, J.: Stakeholder management studies in mega construction projects: A review and future directions, Int. J. Proj. Manag., 33, 446–457, https://doi.org/10.1016/j.ijproman.2014.08.007, 2015.
Mu, L., Bai, T., Liu, D., and Li, L.: Impact of Climate Change on Water Diversion Risk of Inter-Basin Water Diversion Project, Water Resour. Manag., 38, 2731–2752, https://doi.org/10.1007/s11269-024-03777-0, 2024.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual models part I — A discussion of principles, J. Hydrol., 3, 282–290, https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Ouyang, S., Qin, H., Shao, J., Zhang, R., and Dai, M.: Operation Mode of Danjiangkou Reservoir under Water Diversion Conditions of South-to-North Water Diversion Middle Route Project, IOP Conf. Ser.-Mater. Sci. Eng., 366, https://doi.org/10.1088/1757-899X/366/1/012010, 2018.
Ouyang, S., Qin, H., Shao, J., Lu, J., Bing, J., Wang, X., and Zhang, R.: Multi-objective optimal water supply scheduling model for an inter-basin water transfer system: the South-to-North Water Diversion Middle Route Project, China, Water Supp., 20, 550–564, https://doi.org/10.2166/ws.2019.187, 2020.
Patrick, C. J., Kominoski, J. S., McDowell, W. H., Branoff, B., Lagomasino, D., Leon, M., Hensel, E., Hensel, M. J. S., Strickland, B. A., Aide, T. M., Armitage, A., Campos-Cerqueira, M., Congdon, V. M., Crowl, T. A., Devlin, D. J., Douglas, S., Erisman, B. E., Feagin, R. A., Geist, S. J., Hall, N. S., Hardison, A. K., Heithaus, M. R., Hogan, J. A., Hogan, J. D., Kinard, S., Kiszka, J. J., Lin, T., Lu, K., Madden, C. J., Montagna, P. A., O'Connell, C. S., Proffitt, C. E., Reese, B. K., Reustle, J. W., Robinson, K. L., Rush, S. A., Santos, R. O., Schnetzer, A., Smee, D. L., Smith, R. S., Starr, G., Stauffer, B. A., Walker, L. M., Weaver, C. A., Wetz, M. S., Whitman, E. R., Wilson, S. S., Xue, J., and Zou, X.: A general pattern of trade-offs between ecosystem resistance and resilience to tropical cyclones, Sci. Adv., 8, eabl9155, https://doi.org/10.1126/sciadv.abl9155, 2022.
Qiu, H., Chen, L., Zhou, J., He, Z., and Zhang, H.: Risk analysis of water supply-hydropower generation-environment nexus in the cascade reservoir operation, J. Clean. Prod., 283, 124239, https://doi.org/10.1016/j.jclepro.2020.124239, 2021.
Quer, A. M. I., Larsson, Y., Johansen, A., Arias, C. A., and Carvalho, P. N.: Cyanobacterial blooms in surface waters – Nature-based solutions, cyanotoxins and their biotransformation products, Water Res., 251, 121122, https://doi.org/10.1016/j.watres.2024.121122, 2024.
Rousseeuw, P. J. and Leroy, A. M.: Robust Regression and Outlier Detection, John Wiley & Sons, New York, https://doi.org/10.1002/0471725382, 1987.
Sanders, K. T. and Webber, M. E.: Evaluating the energy consumed for water use in the United States, Environ. Res. Lett., 7, 034034, https://doi.org/10.1088/1748-9326/7/3/034034, 2012.
Sheng, J., Zhang, R., and Yang, H.: Inter-basin water transfers and water rebound effects: The South-North water transfer Project in China, J. Hydrol., 638, 131516, https://doi.org/10.1016/J.JHYDROL.2024.131516, 2024.
Siddik, M. A. B., Dickson, K. E., Rising, J., Ruddell, B. L., and Marston, L. T.: Interbasin water transfers in the United States and Canada, Sci. Data, 10, 27, https://doi.org/10.1038/s41597-023-01935-4, 2023.
Stickler, C. M., Coe, M. T., Costa, M. H., Nepstad, D. C., McGrath, D. G., Dias, L. C. P., Rodrigues, H. O., and Soares-Filho, B. S.: Dependence of hydropower energy generation on forests in the Amazon Basin at local and regional scales, P. Natl. Acad. Sci. USA, 110, 9601–9606, https://doi.org/10.1073/pnas.1215331110, 2013.
Stone, R. and Jia, H.: Hydroengineering – Going against the flow, Science, 313, 1034–1037, https://doi.org/10.1126/science.313.5790.1034, 2006.
Su, L., Lettenmaier, D. P., Pan, M., and Bass, B.: Improving runoff simulation in the Western United States with Noah-MP and VIC models, Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, 2024.
Tang, M., Xu, W., Zhang, C., Shao, D., Zhou, H., and Li, Y.: Risk assessment of sectional water quality based on deterioration rate of water quality indicators: A case study of the main canal of the Middle Route of South-to-North Water Diversion Project, Ecol. Indic., 135, 108776, https://doi.org/10.1016/j.ecolind.2022.108592, 2022.
Tang, X., Huang, Y., Pan, X., Liu, T., Ling, Y., and Peng, J.: Managing the water-agriculture-environment-energy nexus: Trade-offs and synergies in an arid area of Northwest China, Agr. Water Manage., 295, 108776, https://doi.org/10.1016/j.agwat.2024.108776, 2024.
Tao, H., Gemmer, M., Song, Y., and Jiang, T.: Ecohydrological responses on water diversion in the lower reaches of the Tarim River, China, Water Resour. Res., 44, W08422, https://doi.org/10.1029/2007WR006186, 2008.
Tauro, F.: River basins on the edge of change Water scarcity after the Millennium Drought reveals the finite resilience of water systems, Science, 372, 680–681, https://doi.org/10.1126/science.abi8770, 2021.
Tennant, D. L.: Instream Flow Regimens for Fish, Wildlife, Recreation and Related Environmental Resources, Fisheries, 4, 6–10, https://doi.org/10.1577/1548-8446(1976)001<0006:IFRFFW>2.0.CO;2, 1976.
Tharme, R. E.: A global perspective on environmental flow assessment: Emerging trends in the development and application of environmental flow methodologies for rivers, River Res. Appl., 19, 397–441, https://doi.org/10.1002/rra.736, 2003.
Tian, J., Guo, S. L., Wang, J., Wang, H. Y., Pan, Z. K.: Preemptive warning and control strategies for algal blooms in the downstream of Han River, China, Ecol. Indic., 142, 109190, https://doi.org/10.1016/J.ECOLIND.2022.109190, 2022.
Wang, C., Li, Z., Ni, X., Shi, W., Zhang, J., Bian, J., and Liu, Y.: Residential water and energy consumption prediction at hourly resolution based on a hybrid machine learning approach, Water Res., 246, 120733, https://doi.org/10.1016/j.watres.2023.120733, 2023.
Wang, G. Q., Zhang, J. Y., Jin, J. L., Pagano, T. C., Calow, R., Bao, Z. X., Liu, C. S., Liu, Y. L., and Yan, X. L.: Assessing water resources in China using PRECIS projections and a VIC model, Hydrol. Earth Syst. Sci., 16, 231–240, https://doi.org/10.5194/hess-16-231-2012, 2012.
Wang, H., Liu, J., Klaar, M., Chen, A., Gudmundsson, L., and Holden, J.: Anthropogenic climate change has influenced global river flow seasonality, Science, 383, 1009–1014, https://doi.org/10.1126/science.adi9501, 2024.
Wei, J., Zhang, Q., Yin, Y., Peng, K., Wang, L., Cai, Y., and Gong, Z.: Limited Impacts of Water Diversion on Micro-eukaryotic Community along the Eastern Route of China's South-to-North Water Diversion Project, Water Res., 262, 122109, https://doi.org/10.1016/j.watres.2024.122109, 2024.
Wei, N., Yang, F. L., Lu, K. M., Xie, J. C., Zhang, S. F.: A Method of Multi-Objective Optimization and Multi-Attribute Decision-Making for Huangjinxia Reservoir, Appl. Sci., 12, 6300, https://doi.org/10.3390/APP12136300, 2022.
Wei, X., Zhang, H., Singh, V. P., Dang, C., Shao, S., and Wu, Y.: Coincidence probability of streamflow in water resources area, water receiving area and impacted area: implications for water supply risk and potential impact of water transfer, Hydrol. Res., 51, 1120–1135, https://doi.org/10.2166/nh.2020.106, 2020.
Wu, J., Luo, J., Du, X., Zhang, H., and Qin, S.: Optimizing water allocation in an inter-basin water diversion project with equity-efficiency tradeoff: A bi-level multiobjective programming model under uncertainty, J. Clean. Prod., 371, 133606, https://doi.org/10.1016/j.jclepro.2022.133606, 2022.
Wu, Z., Mei, Y., Cheng, B., and Hu, T.: Use of a Multi-Objective Correlation Index to Analyze the Power Generation, Water Supply and Ecological Flow Mutual Feedback Relationship of a Reservoir, Water Resour. Manag., 35, 465–480. https://doi.org/10.1007/s11269-020-02726-x, 2021.
Wu, Z., Liu, D., Mei, Y., Guo, S., Xiong, L., Liu, P., Chen, J., Yin, J., and Zeng, Y.: A nonlinear model for evaluating dynamic resilience of water supply hydropower generation-environment conservation nexus system, Water Resour. Res., 59, e2023WR034922. https://doi.org/10.1029/2023WR034922, 2023.
Xia, R., Wang, G., Zhang, Y., Yang, P., Yang, Z., Ding, S., Jia, X., Yang, C., Liu, C., Ma, S., Lin, J., Wang, X., Hou, X., Zhang, K., Gao, X., Duan, P., and Qian, C.: River algal blooms are well predicted by antecedent environmental conditions, Water Res., 185, 116221, https://doi.org/10.1016/j.watres.2020.116221, 2020.
Xu, F., Jia, Y., Niu, C., Liu, J., and Hao, C.: Changes in Annual, Seasonal and Monthly Climate and Its Impacts on Runoff in the Hutuo River Basin, China, Water, 10, w10030278, https://doi.org/10.3390/w10030278, 2018.
Yan, Z., Zhou, Z., Liu, J., Wen, T., Sang, X., and Zhang, F.: Multiobjective Optimal Operation of Reservoirs Based on Water Supply, Power Generation, and River Ecosystem with a New Water Resource Allocation Model, J. Water Res. Pl.-ASCE, 146, 12, https://doi.org/10.1061/(ASCE)WR.1943-5452.0001302, 2020.
Yang, Q., Xie, P., Shen, H., Xu, J., Wang, P., and Zhang, B.: A novel flushing strategy for diatom bloom prevention in the lower-middle Hanjiang River, Water Res., 46, 2525–2534, https://doi.org/10.1016/j.watres.2012.01.051, 2012.
Yang, Y., Chen, S., Zhou, Y., Ma, G., Huang, W., and Zhu, Y.: Method for quantitatively assessing the impact of an inter-basin water transfer project on ecological environment-power generation in a water supply region, J. Hydrol., 618, 129250, https://doi.org/10.1016/j.jhydrol.2023.129250, 2023.
Yeste, P., García-Valdecasas Ojeda, M., Gámiz-Fortis, S. R., Castro-Díez, Y., Bronstert, A., and Esteban-Parra, M. J.: A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments, Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, 2024.
Zeng, Y., Liu, D., Guo, S., Xiong, L., Liu, P., Chen, J., Yin, J., Wu, Z., and Zhou, W.: Assessing the effects of water resources allocation on the uncertainty propagation in the water-energy-food-society (WEFS) nexus, Agr. Water Manage., 282, https://doi.org/10.1016/j.agwat.2023.108279, 2023.
Zhang, B. H. M. M.: Selection of installed capacity of XinglongHydropower Station, Hydropower and New Energy, 1, 66–68, https://doi.org/10.13622/j.cnki.cn42-1800/tv.2008.01.020, 2008 (in Chinese).
Zhang, J., Xu, L., Yu, B., and Li, X.: Environmentally feasible potential for hydropower development regarding environmental constraints, Energ. Policy, 73, 552–562, https://doi.org/10.1016/j.enpol.2014.04.040, 2014.
Zhang, J., Bing, J., Li, X., Guo, L., Deng, Z., Wang, D., and Liu, L.: Inter-basin water transfer enhances the human health risk of heavy metals in the middle and lower Han River, China, J. Hydrol., 613, 128423, https://doi.org/10.1016/j.jhydrol.2022.128423, 2022.
Zhao, D., Liu, J., Sun, L., Ye, B., Hubacek, K., Feng, K., and Varis, O.: Quantifying economic-social-environmental trade-offs and synergies of water-supply constraints: An application to the capital region of China, Water Res., 195, 116986–116986, https://doi.org/10.1016/j.watres.2021.116986, 2021.
Zhao, Z., Zuo, J., and Zillante, G.: Transformation of water resource management: a case study of the South-to-North Water Diversion project, J. Clean. Prod., 163, 136–145, https://doi.org/10.1016/j.jclepro.2015.08.066, 2017.
Zitzler, E.: Two decades of evolutionary multi-criterion optimization: A glance back and a look ahead, in: 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision Making, Honolulu, HI, USA, 318–318, https://doi.org/10.1109/MCDM.2007.369107, 2007.
Short summary
The unclear feedback loops of water supply–hydropower generation–environmental conservation (SHE) nexuses with inter-basin water diversion projects (IWDPs) increase the uncertainty in the rational scheduling of water resources for water receiving and water donation areas. To address the different impacts of IWDPs on dynamic SHE nexuses and explore synergies, a framework is proposed to identify these effects across the different temporal and spatial scales in a reservoir group.
The unclear feedback loops of water supply–hydropower generation–environmental conservation...
